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Gas sensor array based on carbon-based thin-film transistor for selective detection of indoor harmful gases

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Rare Metals 2024年第9期43卷 4401-4411页

作者： Can Liu Yu Sun Jia-Yi Guo Xiu-Lei Li Lu Tao Jin-Yong Hu Jue-Xian Cao Ping-Hua Tang Yong Zhang school of Electrical and information engineering Hunan Institute of EngineeringXiangtan 411104China physics and Optoelectronics&Hunan Institute of Advanced Sensing and information Technology Xiangtan UniversityXiangtan 411105China

The identification of indoor harmful gases is imperative due to their significant threats to human health and *** achieve accurate identification,an effective strategy of constructing a sensor array combined with the pattern recognition algorithm is ***-based thin-film transistors are selected as the sensor array unit,with semiconductor carbon nanotubes(CNTs)within the TFT channels modified with different metals(Au,Cu and Ti)for selective responses to NH_(3),H_(2)S and HCHO,*** accurate gas species identification,an identification mode that combines linear discriminant analysis algorithms and logistic regression classifier is *** test results demonstrate that by preprocessing the sensor array’s sensing data with the LDA algorithm and subsequently employing the LR classifier for identification,a 100%recognition rate can be achieved for three target gases(NH3,H2S and HCHO).This work provides significant guidance for future applications of chip-level gas sensors in the realms of the Internet of Things and Artificial Intelligence.

关键词： Carbon-based thin-film transistors Gas sensor arrays Semiconductor carbon nanotubes Multi-gas detection Linear discriminant analysis

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On the size generalizibility of graph neural networks for learning resource allocation

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Science China(information Sciences) 2024年第4期67卷 239-254页

作者： Jiajun WU Chengjian SUN Chenyang YANG Beihang University school of Electronics and information engineering

Size generalization is important for learning resource allocation policies in wireless systems with time-varying scales. If a neural network for learning a wireless policy is not generalizable to the size of its input, it has to be re-trained whenever the system scale changes, which hinders its practical use due to the unaffordable training costs. Graph neural networks(GNNs) have been shown with size generalization ability empirically when optimizing resource allocation. Yet, are GNNs naturally size generalizable? In this paper,we argue that GNNs are not always size generalizable for resource allocation. We find that the aggregation and activation functions of the GNNs for learning a class of wireless policies play a key role in their size generalization ability. We take the GNN with the mean aggregator, called mean-GNN, as an example to reveal a size generalization condition. To demonstrate how to satisfy the condition, we learn power and bandwidth allocation policies for ultra-reliable low-latency communications and show that selecting or pretraining the activation function in the output layer of mean-GNN can make the GNN size *** results validate our analysis and evaluate the performance of the learned policies.

关键词： size generalization graph neural networks resource allocation permutation equivariance

Self-powered flexible fingerprint-recognition display based on a triboelectric nanogenerator

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Nano Research 2024年第4期17卷 3021-3028页

作者： Wandi Chen Haonan Wang Yibin Lin Xinyan Gan Heng Tang Yongai Zhang Qun Yan Tailiang Guo Xiongtu Zhou Chaoxing Wu school of physics and information engineering Fuzhou UniversityFuzhou 350108China Fujian Science&Technology Innovation Laboratory for Optoelectronic information of China Fuzhou 350116China

In the time of Internet of Things(IoT),alternating current electroluminescence(ACEL)has unique advantages in the fields of smart display and human–computer ***,their reliance on external high-voltage AC power supplies poses challenges in terms of wearability and limits their practical *** paper proposed an innovative scheme for preparing a feather triboelectric nanogenerator(F-TENG)using recyclable and environmentally friendly *** highest open-circuit voltage,short-circuit current,and transferred charge of SF6-treated F-TENGs can reach 449 V,63μA,and 152 nC,which enables easy lighting of BaTiO_(3)^(-)doped ACEL *** a human electrical potential,a single-electrode F-TENG is combined with ACEL device for self-powered fingerprint recognition *** works achieve self-powered flexible wearable ACEL devices,which are not only efficient and portable but also have good application prospects in the human–computer interaction,functional displays,and wearable electronic devices.

关键词： alternating current electroluminescent triboelectric nanogenerator feather reactive ion etching fingerprint recognition

Dynamic behavior analysis, color image encryption and circuit implementation of a novel complex memristive system

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Optoelectronics Letters 2024年第3期20卷 183-192页

作者： XIONG Li WANG Xuan ZHANG Xinguo HE Tongdi school of physics and Electromechanical engineering Hexi UniversityZhangye 734000China school of information Science and engineering Dalian Polytechnic UniversityDalian 116034China school of information Science and engineering Lanzhou UniversityLanzhou 730000China

This paper is devoted to introduce a novel four-dimensional memristor-involved system and its applications in image encryption and chaotic circuit. The typical dynamical behaviors of the memristor-involved system are explored, such as chaotic phase potraits, Lyapunov exponent spectrum(LES), bifurcation diagram(BD) and complexity analysis. Then a color image encryption algorithm is designed. In this algorithm, the sequences generated by the four-dimensional memristor-involved system are used in scrambling and diffusion algorithm for three channels.

关键词： image system chaotic

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BioKG-CMI: a multi-source feature fusion model based on biological knowledge graph for predicting circRNA-miRNA interactions

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Science China(information Sciences) 2024年第8期67卷 343-344页

作者： Mengmeng WEI Lei WANG Yang LI Zhengwei LI Bowei ZHAO Xiaorui SU Yu WEI Zhuhong YOU school of Computer Science and Technology China University of Mining and Technology school of information Science and engineering Zaozhuang University school of Computer Science and information engineering Hefei University of Technology Xinjiang Technical Institute of physics & Chemistry Chinese Academy of Sciences school of information engineering Xijing University school of Computer Science Northwestern Polytechnical University

Increasing experimental evidence has shown that circRNA has the potential to serve as a biomarker for disease diagnosis and prognosis, especially in cancer [1]. circ RNA actively participates in numerous pathological processes by serving as an miRNA sponge. Consequently, the precise prediction of circRNA-miRNA interactions(CMIs) is crucial for narrowing down the scope of biological experiments and expediting the research and development of disease treatments.

关键词： Knowledge graph

Protein acetylation sites with complex-valued polynomial model

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Frontiers of Computer Science 2024年第3期18卷 217-226页

作者： Wenzheng BAO Bin YANG school of information engineering Xuzhou University of TechnologyXuzhou 221018China school of information Science and engineering Zaozhuang UniversityZaozhuang 277160China

Protein acetylation refers to a process of adding acetyl groups(CH3CO-)to lysine residues on protein *** one of the most commonly used protein post-translational modifications,lysine acetylation plays an important role in different *** our study,we developed a humanspecific method which uses a cascade classifier of complexvalued polynomial model(CVPM),combined with sequence and structural feature descriptors to solve the problem of imbalance between positive and negative *** gene expression programming and differential evolution are utilized to search the optimal CVPM *** also made a systematic and comprehensive analysis of the acetylation data and the prediction *** performances of our proposed method are 79.15%in Sp,78.17%in Sn,78.66%in ACC 78.76%in F1,and 0.5733 in MCC,which performs better than other state-of-the-art methods.

关键词： protein acetylation complex-valued polynomial model machine learning

Visible Light Indoor Positioning System Based on Pisarenko Harmonic Decomposition and Neural Network

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Chinese Journal of Electronics 2024年第1期33卷 195-203页

作者： Li ZHAO Yi REN Qi WANG Lange DENG Feng ZHANG school of Electronic information engineering Xi’an Technological University

Visible-light indoor positioning is a new generation of positioning technology that can be integrated into smart lighting and optical communications. The current received signal strength(RSS)-based visible-light positioning systems struggle to overcome the interferences of background and indoor-reflected noise. Meanwhile, when ensuring the lighting, it is impossible to use the superposition of each light source to accurately distinguish light source information; furthermore, it is difficult to achieve accurate positioning in complex indoor environments. This study proposes an indoor positioning method based on a combination of power spectral density detection and a neural network. The system integrates the mechanism for visible-light radiation detection with RSS theory, to build a back propagation neural network model fitting for multiple reflection channels. Different frequency signals are loaded to different light sources at the beacon end, and the characteristic frequency and power vectors are obtained at the location end using the Pisarenko harmonic decomposition method. Then, a complete fingerprint database is established to train the neural network model and conduct location tests. Finally, the location effectiveness of the proposed algorithm is verified via actual positioning experiments. The simulation results show that, when four groups of sinusoidal waves with different frequencies are superimposed with white noise, the maximum frequency error is 0.104 Hz and the maximum power error is 0.0362 W. For the measured positioning stage, a 0.8 m × 0.8 m × 0.8 m solid wood stereoscopic positioning model is constructed, and the average error is 4.28 cm. This study provides an effective method for separating multi-source signal energies, overcoming background noise, and improving indoor visible-light positioning accuracies.

关键词： Neural networks Measurement uncertainty Position measurement Harmonic analysis Light emitting diodes Frequency estimation Indoor positioning systems

A single micro-LED manipulation system based on micro-gripper

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Nanotechnology and Precision engineering 2024年第2期7卷 45-52页

作者： Jie Bai Pingjuan Niu Erdan Gu Jianming Li Clarence Augustine TH Tee school of Mechanical engineering Tiangong University school of Electronic and information engineering Tiangong University Institute of Photonics University of Strathclyde Tianjin Key Laboratory of Micro Low Gravity Environment Simulation Technology Tianjin Aerospace Electromechanical Equipment Research Institute Department of Electrical and information engineering School of Physics and Electrical Information EngineeringZhejiang Normal University

Micro-LEDs(μLEDs) have advantages in terms of brightness, power consumption, and response speed. In addition, they can also be used as micro-sensors implanted in the body via flexible electronic skin. One of the key techniques involved in the fabrication of μLED-based devices is transfer printing. Although numerous methods have been proposed for transfer printing, improving the yield of μLED arrays is still a formidable task. In this paper, we propose a novel method for improving the yield of μLED arrays transferred by the stamping method, using an innovative design of piezoelectrically driven asymmetric micro-gripper. Traditional grippers are too large to manipulate μLEDs, and therefore two micro-sized cantilevers are added at the gripper tips. A μLED manipulation system is constructed based on the micro-gripper together with a three-dimensional positioning system. Experimental results using this system show that it can be used successfully to manipulate μLED arrays.

关键词： Micro-gripper Micro-LED Transfer printing Manipulation

Data-driven active vibration control for helicopter with trailing-edge flaps using adaptive dynamic programming

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Chinese Journal of Aeronautics 2024年第6期37卷 151-166页

作者： Yu CHEN Qun ZONG Xiuyun ZHANG Jinna LI school of Electrical and information engineering Tianjin UniversityTianjin 300072China school of information and Control engineering Liaoning Petrochemical UniversityFushun 113001China

The helicopter Trailing-Edge Flaps(TEFs)technology is one of the recent hot topics in morphing wing *** employing controlled deflection,TEFs can effectively reduce the vibration level of ***,designing specific vibration reduction control methods for the helicopters equipped with trailing-edge flaps is of significant practical *** paper studies the optimal control problem for helicopter-vibration systems with TEFs under the framework of adaptive dynamic programming combined with Reinforcement Learning(RL).Time-delay and disturbances,caused by complexity of helicopter dynamics,inevitably deteriorate the control performance of vibration *** solve this problem,a zero-sum game formulation with a linear quadratic form for reducing vibration of helicopter systems is presented with a virtual *** this context,an off-policy reinforcement learning algorithm is developed to determine the optimal control *** algorithm utilizes only vertical vibration load data to achieve a policy that reduces vibration,attains Nash equilibrium,and addresses disturbances while compensating for time-delay without knowledge of the dynamics of the helicopter *** effectiveness of the proposed method is demonstrated in a virtual platform.

关键词： Active control Adaptive dynamic program-ming Helicopter rotor Vibration control Zero-sum game

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